未验证 提交 c9841fe2 编写于 作者: M MissPenguin 提交者: GitHub

Merge pull request #2606 from littletomatodonkey/dyg/add_db_post

add new db post score calculation method
......@@ -51,6 +51,7 @@ public:
float &ssid);
float BoxScoreFast(std::vector<std::vector<float>> box_array, cv::Mat pred);
float PolygonScoreAcc(std::vector<cv::Point> contour, cv::Mat pred);
std::vector<std::vector<std::vector<int>>>
BoxesFromBitmap(const cv::Mat pred, const cv::Mat bitmap,
......
......@@ -159,6 +159,39 @@ std::vector<std::vector<float>> PostProcessor::GetMiniBoxes(cv::RotatedRect box,
return array;
}
float PostProcessor::PolygonScoreAcc(std::vector<cv::Point> contour,
cv::Mat pred){
int width = pred.cols;
int height = pred.rows;
std::vector<float> box_x;
std::vector<float> box_y;
for(int i=0; i<contour.size(); ++i){
box_x.push_back(contour[i].x);
box_y.push_back(contour[i].y);
}
int xmin = clamp(int(std::floor(*(std::min_element(box_x.begin(), box_x.end())))), 0, width - 1);
int xmax = clamp(int(std::ceil(*(std::max_element(box_x.begin(), box_x.end())))), 0, width - 1);
int ymin = clamp(int(std::floor(*(std::min_element(box_y.begin(), box_y.end())))), 0, height - 1);
int ymax = clamp(int(std::ceil(*(std::max_element(box_y.begin(), box_y.end())))), 0, height - 1);
cv::Mat mask;
mask = cv::Mat::zeros(ymax - ymin + 1, xmax - xmin + 1, CV_8UC1);
cv::Point rook_point[contour.size()];
for(int i=0; i<contour.size(); ++i){
rook_point[i] = cv::Point(int(box_x[i]) - xmin, int(box_y[i]) - ymin);
}
const cv::Point *ppt[1] = {rook_point};
int npt[] = {int(contour.size())};
cv::fillPoly(mask, ppt, npt, 1, cv::Scalar(1));
cv::Mat croppedImg;
pred(cv::Rect(xmin, ymin, xmax - xmin + 1, ymax - ymin + 1)).copyTo(croppedImg);
float score = cv::mean(croppedImg, mask)[0];
return score;
}
float PostProcessor::BoxScoreFast(std::vector<std::vector<float>> box_array,
cv::Mat pred) {
auto array = box_array;
......@@ -235,6 +268,8 @@ PostProcessor::BoxesFromBitmap(const cv::Mat pred, const cv::Mat bitmap,
float score;
score = BoxScoreFast(array, pred);
/* compute using polygon*/
// score = PolygonScoreAcc(contours[_i], pred);
if (score < box_thresh)
continue;
......
......@@ -34,12 +34,18 @@ class DBPostProcess(object):
max_candidates=1000,
unclip_ratio=2.0,
use_dilation=False,
score_mode="fast",
**kwargs):
self.thresh = thresh
self.box_thresh = box_thresh
self.max_candidates = max_candidates
self.unclip_ratio = unclip_ratio
self.min_size = 3
self.score_mode = score_mode
assert score_mode in [
"slow", "fast"
], "Score mode must be in [slow, fast] but got: {}".format(score_mode)
self.dilation_kernel = None if not use_dilation else np.array(
[[1, 1], [1, 1]])
......@@ -69,7 +75,10 @@ class DBPostProcess(object):
if sside < self.min_size:
continue
points = np.array(points)
if self.score_mode == "fast":
score = self.box_score_fast(pred, points.reshape(-1, 2))
else:
score = self.box_score_slow(pred, contour)
if self.box_thresh > score:
continue
......@@ -120,6 +129,9 @@ class DBPostProcess(object):
return box, min(bounding_box[1])
def box_score_fast(self, bitmap, _box):
'''
box_score_fast: use bbox mean score as the mean score
'''
h, w = bitmap.shape[:2]
box = _box.copy()
xmin = np.clip(np.floor(box[:, 0].min()).astype(np.int), 0, w - 1)
......@@ -133,6 +145,27 @@ class DBPostProcess(object):
cv2.fillPoly(mask, box.reshape(1, -1, 2).astype(np.int32), 1)
return cv2.mean(bitmap[ymin:ymax + 1, xmin:xmax + 1], mask)[0]
def box_score_slow(self, bitmap, contour):
'''
box_score_slow: use polyon mean score as the mean score
'''
h, w = bitmap.shape[:2]
contour = contour.copy()
contour = np.reshape(contour, (-1, 2))
xmin = np.clip(np.min(contour[:, 0]), 0, w - 1)
xmax = np.clip(np.max(contour[:, 0]), 0, w - 1)
ymin = np.clip(np.min(contour[:, 1]), 0, h - 1)
ymax = np.clip(np.max(contour[:, 1]), 0, h - 1)
mask = np.zeros((ymax - ymin + 1, xmax - xmin + 1), dtype=np.uint8)
contour[:, 0] = contour[:, 0] - xmin
contour[:, 1] = contour[:, 1] - ymin
cv2.fillPoly(mask, contour.reshape(1, -1, 2).astype(np.int32), 1)
return cv2.mean(bitmap[ymin:ymax + 1, xmin:xmax + 1], mask)[0]
def __call__(self, outs_dict, shape_list):
pred = outs_dict['maps']
if isinstance(pred, paddle.Tensor):
......
......@@ -62,6 +62,7 @@ class TextDetector(object):
postprocess_params["max_candidates"] = 1000
postprocess_params["unclip_ratio"] = args.det_db_unclip_ratio
postprocess_params["use_dilation"] = args.use_dilation
postprocess_params["score_mode"] = args.det_db_score_mode
elif self.det_algorithm == "EAST":
postprocess_params['name'] = 'EASTPostProcess'
postprocess_params["score_thresh"] = args.det_east_score_thresh
......
......@@ -48,6 +48,7 @@ def parse_args():
parser.add_argument("--det_db_unclip_ratio", type=float, default=1.6)
parser.add_argument("--max_batch_size", type=int, default=10)
parser.add_argument("--use_dilation", type=bool, default=False)
parser.add_argument("--det_db_score_mode", type=str, default="fast")
# EAST parmas
parser.add_argument("--det_east_score_thresh", type=float, default=0.8)
parser.add_argument("--det_east_cover_thresh", type=float, default=0.1)
......
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